Rewards for custom data transmissions

ABSTRACT

An example system comprising a computing device to transmit data from a vehicle provisioned with a plurality of hardware computing resources to a decentralized entity, the computing device to receive a custom data selection from the vehicle in response to a conditional request for a particular data set by the decentralized entity, apply a hash function to the custom data selection, transmit the custom data selection to the decentralized entity, verify that the custom data selection fulfills the conditional request of the decentralized entity, and transmit a reward to the vehicle from the decentralized entity in response to the custom data selection having fulfilled the conditional request.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. patent application Ser. No. 16/131,578 filed on Sep. 14, 2018, the contents of which is incorporated herein by reference in its entirety.

BACKGROUND

Data about an edge device may be transmitted to a computing device. The data about the edge device may be received by an entity from the computing device

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example system including a computing device for facilitating rewards for custom data transmissions consistent with the disclosure.

FIG. 2 illustrates an example system including a computing device for facilitating rewards for custom data transmissions consistent with the disclosure.

FIG. 3 illustrates an example flow chart for rewards for custom data transmissions consistent with the disclosure.

FIG. 4 illustrates an example flow diagram for rewards for custom data transmissions consistent with the disclosure.

FIG. 5 illustrates an example of a non-transitory machine-readable memory resource and processing resource for rewards for custom data transmissions consistent with the disclosure.

FIG. 6 illustrates an example method for rewards for custom data transmissions consistent with the disclosure.

DETAILED DESCRIPTION

Edge devices may produce data about themselves or may collect data about their environments which may be received by entities. The entities may use the data from the edge devices to answer relevant questions, predict future outcomes, evaluate plans, etc. For example, an entity may be a business, a person, an organization, or an otherwise interested identifiable party which may be interested in acquiring a particular data set about a device.

As used herein, a “device” refers to an article that is adapted for a particular and/or multiple purpose. A device may include a computing system. A device may include one or more memory resources to store data and/or instructions corresponding with the computing system. An edge device may refer to any device that is located at the edge of a network as opposed to the core (e.g., campus and/or near data center) of the network. A computing system may include one or more processing resources to execute instruction such as instruction corresponding to an operating system (e.g., Linus, Unix, Windows, etc.) to provide common services for applications running on the computing system. Some examples, of devices that include computing systems are personal computers, laptops, tablets, phablets, smartphones, Internet-of-Things (IoT) enabled devices, etc., may be included on a virtualized architecture and/or a non-virtualized architecture. As used herein, “IoT enabled devices” include devices embedded with electronics, software, sensors, actuators, and/or network connectivity which enable such devices to connect to a network and/or exchange data. Examples of IoT enabled devices include vehicles, home appliances, smart home devices, monitoring devices, wearable devices, devices enabling intelligent shopping systems, manufacturing devices, among other cyber-physical systems.

Devices including computing systems may produce data, and data buyers may consider the produced data to be valuable. As used herein, the term “data buyer” refers to entities interested in collecting the data produced by the devices. For example, data buyers may include businesses, manufactures, regulatory agencies, third-parties, public health, public safety, etc. who may be interested in real-time data collection to make decisions, change business practices, analyze outcomes of prior decisions, etc. The data produced by the devices have created a dynamically evolving and fastly changing data driven landscape where the data produced by the devices may be valuable and treated as a commodity by device manufactures and other interested data buyers. For example, the data produced by devices may be bought and sold by manufactures and third parties interested data buyers when data is shared. In these examples, the parties benefiting from the data acquisition are the data buyers and the manufactures. Furthermore, an IoT enabled device may include multiple components (e.g., multiple electrical control units (ECUs) on a vehicle) and each ECU of the multiple ECUs may produce data inherently during operation.

For example, an IoT-enabled device such as a vehicle (e.g., a connected and/or autonomous vehicle that has a computing capability to communicate with an external server and/or a network) may have multiple functional aspects which may be producing data that may be valuable to multiple entities. Therefore, the control over where the produced data goes and a reward for the exchange of the data may be of value to the owner and/ or user of the data. Furthermore, the data produced may increase in value if the interested party is able to request specific data, and the user and/or owner of the device is able to accommodate by customizing the data provided for a mutually agreed upon reward. Therefore, the customization of the data produced by the devices and the real-time data driven reward in exchange for the data may be an incentive for providing specific custom data to a data buyer.

As such, examples discussed herein provide examples, of devices, operators, owners, etc. benefitting from the data that is inherently produced by the use (or non-use) of the device in a controlled custom way. For example, in the context of automotive and aircraft industries, generation of custom data may be sought in various situations as described in the following examples. As used herein, the term “custom data” and/or “custom data selection” refers to a device selectively selecting a particular data set, multiple points of data, a data stream, etc. The custom data selection may be limited or unlimited. For example, a custom data selection may include particular periods of time, geographical locations, operations, etc. As used herein, the term “vehicle” refers to a car (e.g., sedan, van, truck, etc.), a connected vehicle (e.g., a vehicle that has a computing capability to communicate with an external server), an autonomous vehicle (e.g., a vehicle with self-automation capabilities such as self-driving), a drone, a plane, a scooter, a skateboard, a hoverboard, an upright personal vehicle (e.g., a Segway), and/or anything used for transporting people, services, and/or goods.

Some example data buyers may include provisions for a particular data set to be collected from vehicles in exchange for a reward. For example, the particular data set may include a request for data about an amount of rain falling on a vehicle, at a particular geographical location, at a particular time. In this instance, the vehicle may provide a custom data selection based on the particular data set requested to receive the reward. In other examples, the data buyers may be public welfare agencies to collect data related to public safety and the reward may be information that is helpful to the user/operator of the device (e.g. the vehicle). In some instances, the reward may instead or also be of benefit to the data buyer, a third party aside from one or more of the data buyer and user. As, used herein, the term “reward” refers to an element of perceived value. It should be understood, and will be described below, that rewards can encompass a broad range or array of benefits or things returned in exchange for, in some embodiments, customized data. Rewards can be monetary or non-monetary in nature. Some examples of a reward may include information, vouchers, currency, cryptocurrency, coupons, gifts, a statement of gratitude, affirmation, or a conformation of receipt of the custom data selection, access to other offered services, etc. Other examples of a reward can be media, implementation or removal of functionality, behavioral rewards, data itself, data protection, etc. In some embodiments, rewards may be some combination of one or more rewards, types of rewards, levels of rewards, etc.

Moreover, rewards may be weighed or valued in different ways, and can be dynamic. For example, certain captured data may be more valuable if the data is unique or hard to obtain, e.g., a data buyer is not able to access certain types of data or data relating to a certain desired data set(s). Data may be valued in relation to the confidence associated with the accuracy or reliability of the data.

In providing control to the user/owner/operator/device to create custom data in exchange for a reward, it is technically challenging to provide secure custom data selection in real-time and to generate and communicate multiple data points from multiple ECUs that may be requested of the IoT enabled devices, as described in the above examples.

In addressing these technical challenges, some examples as disclosed herein may utilize an on-board computing resource (e.g., a Controller Area Network (CAN bus)) to compile the custom data selection requested by a data buyer and securely communicate it with a computing device (e.g., a Mobile Edge Computing, MEC server). It should be noted that other networks or combinations of networks, such as ethernet, secured and encrypted networks, etc. may be used in place of or in addition to a CAN bus. The MEC server (e.g., a node on a network such as a wireless network and/or an on-board computing device) may transmit the custom data selection from the CAN bus to the data buyer in exchange for a reward. In some examples, the MEC server may apply a hash function to the custom data selection and verify that the contents of the custom data selection has fulfilled the request from the data buyer. The data buyer may utilize a smart contract script (e.g., a command executed by a program) and/or other decentralized applications (DApps), to which they may include the particular data set requested, and the reward offered in exchange for the particular data set. The smart contracts may reside on a decentralized entity which may include a distributed ledger technology (DLT), (e.g., a blockchain with smart contract capabilities) such that the smart contract may be accessed by the computing device (e.g., the MEC server). Furthermore, the MEC server may store the exchange between the device providing the custom data selection and the reward offered by the data buyer as a transaction and store the transaction information as an immutable record on the decentralized entity (e.g., a DLT and/or a blockchain). The data buyers may create, modify, delete or otherwise update provisions (e.g., specifying a condition such as particular combinations of ECUs, dates, times, geographical areas, etc.) using at least one smart contract and/or DApp. In this way, the data provided may be custom, controlled, and provided by the device in exchange for a reward upon mutual agreement. Further, by leveraging the decentralized entity with smart contract capability, the immutable record of the transaction by a particular device and a particular data buyer can be digitally verified against such dynamically changing environments as they are created, modified, deleted or otherwise updated.

FIG. 1 illustrates an example system 100 including a computing device for facilitating rewards for custom data transmissions consistent with the disclosure. FIG. 1 includes an edge device such as a vehicle 102 which may include a computing resource 104 to generate a custom data selection 106 with a computing device 108. The computing device 108 may be communicatively coupled to a decentralized entity 110 which may include a smart contract 112. A smart contract may refer to a computer code running on top of a blockchain containing a set of rules under which the parties to that smart contract agree to interact with each other. If and when the pre-defined rules are met, the agreement is automatically enforced. In this context, the smart contract 112 may be created by a data buyer and provisioned with a conditional request 114 including a particular data set 116, and a reward 118 which may be offered in exchange for the custom data selection 106. When the conditional request 114 is met, the custom data selection 106 defined by the data buyer may be supplied to the computing device 108 and the reward 118 may be provided to the data owner (e.g., owner or operator of the vehicle 102).

The vehicle 102 may include virtualized architecture and/or non-virtualized architecture deployed in the computing resource 104. The vehicle 102 may be provisioned with a plurality of hardware computing resources. For example, the computing resource 104 may include memory resources (and/or possess the ability to perform memory-like functions) to store instructions. The memory resource(s) may be electronic, magnetic, optical, virtual, and/or other physical storage devices that store executable instructions; for example, volatile memory (e.g., RAM, DRAM, SRAM, EPROM, EEPROM, etc.) and/or non-volatile memory (e.g., an HDD, a storage volume, data storage, etc.). In addition, the computing resource 104 may include a processor (and/or possess the ability to execute processor-like functions). For example, the computing resource 104 may include a processor which may be a central processing unit (CPU), a semiconductor-based microprocessor, and/or other hardware devices suitable for retrieval and execution of instructions stored in a memory resource (e.g., in a non-transitory computer readable medium). The example processor may fetch, decode, and execute instructions. As an alternative, or in addition to, retrieving and executing instructions, the example processor may include at least one electronic circuit that may include electronic components for performing the functionality of executed instructions. In some examples, the computing resource 104 deployed on the vehicle 102 may be a Controller Area Network (CAN bus).

As used herein, the term “CAN bus” refers to a computing resource that allows microcontrollers and devices to communicate with each other in applications absent a host computer. For example, the vehicle 102 may include multiple ECUs which may be allowed to communicate with each other via the CAN bus (e.g., the computing resource 104). In other words, each of the multiple ECUs may communicate with each other absent dedicated connection in between. The CAN bus may include processors and memory devices which may allow it to receive transmitted messages and communicate with nodes (e.g., the computing device 108). Further, the CAN bus may provide data about the multiple ECUs (e.g., the custom data selection 106).

As used herein, the term “electronics control unit” and/or “(ECU)”, refers to an embedded system that detects and/or controls operation(s) of an electronic and/or mechanical device. In some examples, an ECU may be a sensor that may detect an operation of an electronic and/or mechanical device. For example, ECU(s) may be included on a vehicle to detect, execute or otherwise control physical operations on a vehicle (e.g., powertrain control module, speed control unit, brake control module, battery management system, biometric data, etc.). The computing resource 104 (e.g., the CAN bus) may provide real-time data from a combination of ECUs which may be compiled into a custom data selection 106 and transmitted to the computing device 108 which may be connected to the vehicle 102 via the computing resource 104. It should be understood that in some embodiments, more centralized compute units may be used in conjunction with or in place of the aforementioned ECU(s).

Vehicle 102 may, in some embodiments, further include one or more sensors 102 a implemented within or as part of vehicle 102. Sensors 102 a may include any sensors, monitors, data loggers, or similar devices that are configured to receive and/or generate signals that indicate (or may be used to infer/can be used to derive) operating conditions of vehicle 102 and/or related conditions or characteristics, such as road conditions, weather conditions, etc., internal or external to vehicle 102. These may include but are not limited to accelerator pedal actuation amount, engine and/or motor speed, vehicle speed, road load, brake operation amount/pressure, battery state of charge (SOC), fuel efficiency, location, traffic conditions, vehicle component use/health, etc. These signals may also include operator (driver) and/or passenger condition/health, operator and/or passenger action(s), such as movement, use of devices, such as passenger use (or dis-use) of a smartphone, vehicle infotainment, vehicle safety feature, (as well as how/for what purpose it is used).

For example, in addition to vehicle 102 being an IoT sensor itself, vehicle 102 may include IoT sensors. One or more of sensors 102 a may include their own processing capability to compute results (based on sensed data) that can be transmitted to one or more ECUs (see FIG. 2) Alternatively, one or more of sensors 102 a merely gather information or data (raw information/data) to be transmitted to one or more ECUs. Alternatively still, one or more of sensors 102 a can perform some processing of sensed data as well as transmit or gather raw data for processing by another device, such as one or more ECUs.

Examples of such sensors may include, but are not limited to sonar, radar, proximity sensors, cameras, image sensors, biometric sensors, accelerometers, temperature sensors, etc. One or more of sensors 102 a may be configured to communicate with other ones of sensors 102 a and/or other sensors or devices external to vehicle 102. For example, some of sensors 102 a may be configured to communicate with smart roadway infrastructure via vehicle-to-infrastructure (V2I) communications, vehicle-to-vehicle (V2V) communications. Other ones of sensors 102 a may sense passive objects, features, or characteristics, such as traffic signs, road grade, etc. Computing resource 104 may perform a comparison between vehicle 102-obtained sensor data and that from roadway infrastructure/other vehicles. Data reflecting the results of the comparison may be transmitted to computing device 108 to allow computing device to verify that a custom data selection fulfills a conditional request.

One or more of sensors 102 a may, when gathering or collecting data (or when sending signals representative of the gathered/collected data), commensurately sense time, or add a timestamp, or other related information or indicators to the data. In some embodiments, subsequent devices, such as an ECU may append temporal metadata to the sensed data.

Vehicle 102 may further include a personal computing device or mobile device 105, such as a smartphone belonging to and/or being used by a passenger or driver of vehicle 102. Mobile device 105 may be a sensor, such as one of sensors 102 a in and of itself. In some embodiments, mobile device 105 may comprise its own sensors or data gathering devices, such as its camera(s), global positioning system (GPS) receiver, accelerometer, etc. It may, in some embodiments, act as a corollary to an ECU of vehicle 102, or it may be act as one of the ECUs of vehicle 102. In some embodiments, mobile device 105 may be another computing resource like computing resource 104 or instance of computing resource 104. In some embodiments, one or more aspects or functionality associated with the various mechanisms disclosed herein may be shared by mobile device 105. For example, one or more sensors 102 a may be V2V or V2I-based sensors, and when out of coverage with appropriate vehicles and/or roadway infrastructure, functionality may be shifted or handed off to mobile device 105. For example, the computing device 108 may receive the custom data selection 106 from the vehicle 102 in response to the vehicle 102 having met the conditional request 114 of a smart contract 112. As used herein, the term “computing device” refers to a device that is adapted to transmit and/or receive signaling, and to process information within such signaling across a network. For example, the computing device 108 may receive the custom data selection 106 and securely transmit it to the decentralized entity 110 with a deployed smart contract 112 (created by a data buyer). The computing device 108 may receive the reward 118 from the smart contract 112 deployed on the decentralized entity 110 and securely transmit the reward 118 to the vehicle 102. In other words, the computing device 108 may act as an intermediary between the vehicle 102 and the data buyer to facilitate the receipt and secure transmission of a custom data selection 106 to the data buyer (via the smart contract 112) and a reward 118 from the data buyer to the vehicle 102. In some examples, the computing device 108 may be a Mobile Edge Computing (MEC) server. In some embodiments, vehicle 102 and computing device 108 may comprise an edge computing system operatively connected to decentralized entity 118. In some embodiments decentralized entity 118 may also be considered an edge device, and may also in part, comprise the edge computing system.

As used herein, the term “Mobile Edge Computing server” and/or “MEC server” refers to a computing device on a node on a network such as a decentralized entity (e.g., DLT and/or a blockchain) and may communicate with the computing resource 104. For example, the vehicle 102 may be moving between two locations, the computing device 108 (e.g., a MEC server) may maintain communication with the vehicle 102 as it is traveling between the two locations. The computing device 108 may apply a hash function to the custom data selection 106 to securely communicate the custom data selection 106 to the smart contract 112 deployed on the decentralized entity 110.

As used herein, the term “hash function” refers to a cryptographic series of numbers and characters to act as a digital fingerprint applied to a piece of information to secure the information, prevent error, and/or be stored with a transaction on the blockchain. For example, a first hash function may be applied by the computing device 108 to the custom data selection 106 such that the hash function may be stored as part of the transaction record on the decentralized entity 110. The custom data selection 106 may be transmitted from the vehicle 102 via the computing device 108 to the data buyer that created the smart contract 112 via a side channel. As used herein, the term “side channel” refers to a communication between the device (e.g., the vehicle 102) and the data buyer. For example, the vehicle 102 may transmit via a side channel, the custom data selection 106 to the data buyer (bypassing the decentralized entity). In some examples, the vehicle 102 may transmit the custom data selection 106 to the data buyer via a side channel and the computing device 108. Either way, in response to receiving the custom data selection 106 from the vehicle 102, the data buyer may execute a second hash function of the custom data selection 106 received and compare the result of the first hash function stored on the decentralized entity 110, and the second hash function executed by the data buyer. The result of this comparison is referred to as a hash value. A hash value result indicating the compared first and second hash functions are the same indicate that there has not been an error in transmission of the custom data selection 106 to the data buyer. In this way, hash functions may secure the customized data selection 106 from tampering, hacking, malicious intent, transmission error, etc. and the hash function may be securely stored with the transaction as a block in a blockchain.

In some examples, the vehicle 102 may compile a custom data selection 106 and the computing device 108 may authenticate the custom data selection 106. As used herein, the term “authenticate” refers to the computing device 108 confirming that the data included in the custom data selection 106 is valid (e.g., from the vehicle 102, contains the correct data, etc.). For example, the computing device 108 may apply a time stamp and/or other metadata to the custom data selection 106 and confirm the vehicle's 102 identity. In some examples, the computing device 108 may utilize a profile related to the vehicle 102 and/or related to mobile 105 to transmit, receive, and/or otherwise authenticate the custom data selection 106.

For example, the vehicle 102 may include a profile which may be shared on the computing device 108. As used herein, the term “profile” refers to data which may be utilized to include information about a device (e.g., the vehicle 102 or mobile device 105). In some examples, the profile may be stored on the decentralized entity and include data about the transaction and the custom data selection 106. For example, the profile may include information about the vehicle 102, such as the make, model, year, color, user, owner, operator, vehicle identification number (VIN), etc. For example, the profile may include further information about the user, owner, operator of vehicle 102, such as age, purchase history/preferences, travel preferences, driving habits/preferences, etc. The computing device may provide a repository for the reward based on the profile and enable a user to view the conditional request 114, which includes the reward 118 and the particular data set 116, requested by a data buyer. The vehicle 102/mobile device 105 may accept the smart contract 112 via the profile and create the custom data selection 106 to fulfill the smart contract 112 utilizing the profile. The vehicle 102/mobile device 105 may receive the reward 118 and store the reward 118 in a repository utilizing the profile. As used herein, the term “accept” refers to a device agreeing to provide data per a request. For example, a vehicle 102/mobile device 105 may accept a smart contract 112 via the computing resource 104, and/or the profile. The profile is further discussed herein in connection with FIG. 2.

As mentioned herein, the computing device 108 may transmit data from the vehicle 102 and/or mobile device 105 provisioned with hardware computing resources 104 to a decentralized entity 110. As used herein, the term “decentralized entity” refers to an open-source, public, distributed computing platform. The decentralized entity may include distributed ledger technology (DLT). The DLT includes a consensus of replicated, shared, and synchronized digital data which may be spread across multiple computing devices. In some examples, the decentralized entity may be a blockchain-based distributed computing platform. For example, a block may include information and may be added to a blockchain as an immutable record, the blocks may be linked together utilizing the hash function applied to the information by the computing device 108. In some examples, the hash function of the custom data selection 106 may be stored with the transaction as an immutable record in a block in the blockchain in the decentralized entity 110. For example, the decentralized entity 110 may include smart contract 112 functionality such that a data buyer may create a smart contract 112 to include a conditional request 114, a particular data set 116, and/or a reward 118 to be offered in exchange for the custom data selection 106. The custom data selection 106 may fulfil the requested particular data set 116, and the transaction and the hash function of the custom data selection 106 may be stored on the blockchain. In another example, the complete custom data selection 106 may be stored on a profile corresponding to the vehicle 102 in the computing device 108.

As used herein, the term “smart contract” is a protocol to digitally facilitate, verify, and/or enforce a negotiation and/or a performance of information in credible transactions. A smart contract script (e.g., a command executed by a program) may be executed by the computing device 108. The smart contract 112 may be generated by a data buyer (e.g., a manufacturer, business, public safety organizations, and/or a legal entity etc.). The data buyer may create the smart contract 112 by stipulating the parameters to fulfill the conditional request 114 and funding the smart contract 112 with the reward 118. In some use cases (such as mass casualty events), it is possible that no reward 118 is funded by the data buyer (e.g., Red Cross organization) that uses the particular data set 116 for public benefits. Therefore, the reward 118 may be an optional component in the conditional request 114. Data buyers may create, modify, delete or otherwise update provisions (e.g., specifying a conditional request 114, requested particular data set 116, and the reward 118 offered in exchange for the fulfillment of the smart contract 112) using a smart contract 112. Therefore, by leveraging the smart contract 112 capability, and the immutable record capability of the decentralized entity 110 the custom data selection 106 created by the vehicle 102 may be digitally verified against such dynamically changing requests from the data buyer as they are created, modified, deleted or otherwise updated and the vehicle 102 may collect the reward 118. As mentioned herein, the data buyer may provide a smart contract 112 provisioned with a conditional request 114.

For example, a data buyer may create a smart contract 112 to include a conditional request 114. As used herein, the term “conditional request” refers to parameters that when met fulfill the conditional request 114 to release the reward 118. The conditional request 114 may be created by the data buyer and provided to the vehicle 102 by the computing device 108. For example, a conditional request 114 may include a reward 118 offered in exchange for a particular data set 116, and other parameters such as a particular time, day, distance, geographical region, etc. which may correspond to the particular data set 116 for the smart contract 112 to be fulfilled. As used herein, the term “fulfilled” refers to a custom data selection 106 provided to include the particular data set 116 of the conditional request 114 of the smart contract 112. For example, a particular data set 114 may be rainfall data on a two Kilometer (Km) stretch of road after the sun has gone down. In this example, the vehicle 102 may fulfill the conditional request 114 and receive the reward 118 when the vehicle creates the custom data selection 106 to include the particular data set 116. In other words, the custom data selection 106 may include a combination of data from one ECU or multiple ECU(s) which may be created by the vehicle 102 based on the particular data set 116 requested in the conditional request 114 of the smart contract 112. In some examples, since the computing device 108 is communicatively connected to both the vehicle 102 (and/or mobile device 105) and the decentralized entity 110, the vehicle 102/mobile device 105 may monitor the computing device 108 for available smart contracts 112.

As used herein, the term “monitor” refers to a device observing a computing device for smart contracts. For example, the vehicle 102, via the computing resource 104 and/or the profile, may monitor the computing device 108 for smart contracts 112 included on the decentralized entity 110. In some embodiments, mobile device 105 may monitor the computing device 108 for smart contracts 112. As used herein, the term “available” refers to a smart contract 112 that the vehicle 102 and/or mobile device 105 is capable of fulfilling. For example, the computing resource 104 of the vehicle 102 may, via the profile, determine that the vehicle 102 is capable of fulfilling a smart contract 112. The computing resource 104 of the vehicle 102 may, via the profile, select the available smart contract 112 and agree to provide the particular data set 116 in exchange for the reward 118. The vehicle 102 may create a custom data selection 106 based on the requested particular data set 116. The computing device 108 may receive the custom data selection 106 from the vehicle 102 in response to the conditional request for the particular data set 116 requested by the smart contract 112 on the decentralized entity 110. In other words, the custom data selection 106 is data that has been selected by the vehicle 102 in response to an agreement to provide the custom data selection 106 responsive to a request by a data buyer for the particular data set 116. The computing device 108 may authenticate the custom data selection 106.

For example, the computing device 108 may authenticate the custom data selection 106 by applying metadata (e.g., a time stamp) indicating a time the custom data selection 106 was created and/or details about the vehicle 102 that created the custom data selection 106. The authenticated custom data selection 106 may be used to verify that the custom data selection 106 fulfills the conditional request 114 of the smart contract 112 included on the decentralized entity 110. For example, the custom data selection 106 may be transmitted by the computing device 108 to the decentralized entity 110 to be verified by the smart contract 112. The smart contract 112 may compare the authenticated custom data selection 106 to the conditional request 114 to determine if the particular data set 116 requested was met by the custom data selection 106. The computing device 108 may apply a hash function to the custom data selection 106. The hash function of the custom data selection 106 may be stored with the transaction as an immutable record on the blockchain of the decentralized entity 110. The vehicle 102 may transmit, via the computing device 108 the custom data selection to the data buyer via a side channel. If the data buyer determines via the hash value and the smart contract 112 that the conditional request 114 has been fulfilled, the decentralized entity 110 may transmit, via the smart contract 112, the reward 118, to the computing device 108. The computing device 108 may transmit the reward 118 to the vehicle 102 from the decentralized entity 110 in response to the custom data selection 106 having fulfilled the conditional request 114. The vehicle 102 may receive the reward 118 in the profile, in this way, the data buyer may receive specific custom data which may be more valuable than wholesaled non-specific data, and the user/operator may directly benefit by receiving a reward 118 in exchange for the specific custom data selection 106. In some examples, the requested particular data set 116 may include multiple combinations of ECU information thus the custom data selection 106 may be created by the vehicle 102 specifically for the smart contract 112.

For example, the conditional request 114 for the particular data set 116 may include conditions related to a global positioning system (GPS) fence and the particular data set 116 requested may include data from an ECU measuring the shocks and the speed of the vehicle 102 when the vehicle 102 is within the GPS fence. In this example, vehicle may create the custom data selection 106 by agreeing to share the ECU information about the shocks and the speed of the vehicle 102 during the time period when the vehicle is within the GPS fence. In some examples, the custom data selection 106 may be a stream of data from an ECU of the vehicle 102 over a period of time. In some embodiments, the conditional request 114 for the particular data set 116 may include current road or travel conditions (including, for example, weather, traffic, and the like, driving habits of neighboring vehicles, and the like). Vehicle 102 and/or mobile device 105 may create custom data selection 106 by agreeing to share not only ECU information, but external information sensed by or via vehicle 102 (by way of sensors 102 a) and/or mobile device 105. For example, camera or image information captured by a camera of vehicle 102 may be enhanced or supplemented (or in some embodiments, validated) with camera information captured by a camera of mobile device 10.

As used herein, the term “stream” refers to a data that can be continuously collected for a period of time. For example, the conditional request 114 for the particular data set 116 includes conditions related to a time period and the particular data set 116 requested includes data related to diagnostic services for an electronics control unit (ECU) of the vehicle 102. In the above example, the vehicle 102 may monitor the computing device 108 for an available smart contract 112. The vehicle 102 may determine that a smart contract 112 is offering a reward 118 in the form of a discount on an oil change for the vehicle 102 in exchange for the conditional request 114 of supplying a data stream of brake pad usage for a period of time. For example, the vehicle 102 may create a custom data selection 106 to include the ECU (e.g., the brake pad) data stream relating to the diagnostic service (brake pad usage) for a specific time period (e.g., one hour). Thus, the data buyer gets specific potentially useful information and the vehicle 102 directly benefits by receiving the reward 118 for the discounted oil change. In accordance with the road conditions example, the captured data may shared with a data buyer, such as a navigation service provider, vehicle manufacturer, or the like, to be used in providing up-to-date, real-time, dynamic navigational updates, map updates, real-time traffic warnings/alerts, etc. In some embodiments, such information can be provided to a municipality or other entity interested in road/traffic conditions data that can be used to update traffic signal timing, improve roadway infrastructure, etc. In some embodiments, the driving experience can be gamified, in which greater rewards may be given for more data. That is, a user of vehicle 102 may be incentivized to travel longer, travel a route for which data is desired, etc. with reward 118.

In another example, the conditional request 114 for the particular data set 116 includes conditions related to a geographical location and the particular data set 116 requested includes data related to biometric sensors included in the vehicle 102. In this instance, assume the geographical location is a 100 Km radius of a particular location and the biometric sensors are related to a measurement of sleepiness of an operator of the vehicle 102, and the reward 118 is a discounted rate for lodging. The vehicle 102 may accept the smart contract 112 and provide the custom data selection 106 when biometric ECUs of the vehicle 102 detect sleepiness of the operator of the vehicle 102. Thus, the data buyer may receive a specific particular data set 116 from the vehicle 102 within the specific 100 Km radius, and the vehicle 102 may directly benefit by receiving the reward 118 for the discounted rate for lodging. In other examples, a data buyer may be interested in biometric data to gauge the number of individuals in a vehicle 102 and offer a reward 118 of information about parking. In another example, the vehicle 102 may be stationary, and the biometric data may be used in the custom data selection 106 to determine the temperature of humans or animals inside the vehicle 102 and the reward 118 may be an alert when the temperature reaches a particular level.

In another example, the conditional request 114 for the particular data set 116 requested by the smart contract 112 included on the decentralized entity 110 is related to telematics corresponding to a particular geographical area. In this instance assume that the conditional request 114 is a particular geographical area of 1,000 Km. Further assume the particular data set 116 requested is the number of transmission between a radio in the vehicle 102 with a dispatch unit within the 1,000 Km area, and the particular data set 116 requested is the transmission of a combination of ECUs of the vehicle 102 to the dispatch. In some examples, the reward 118 may be information related to public service, public health, safety, road conditions, etc.

For example, sometimes environmental conditions may affect the safety of device operation and a data buyer may be a non-profit (e.g., a public service entity) requesting specific information in the interest of public safety. In this instance, the conditional request 114 for the particular data set 116 may include conditions related to a geographical location (and/or a time period) and the particular data set 116 requested may include data related to environmental conditions. Specifically, the data buyer may be a public safety entity, the geographical location may be a GPS location, and the particular data set 116 may be snowfall at the GPS location during a period of time. The vehicle 102 may accept the smart contract 112 and provide a custom data selection 106 compiled from ECU data from the computing resource 104. In some examples, the reward 118 is one of information relating to the environment where the vehicle is located, a warning, an advisory, or combinations thereof. For example, the reward 118 may include data relating to nearby shelter locations or other public service announcements relating to public safety. Specifically, in this instance the data buyer may benefit from real-time, custom data that may be uniquely relevant to the data buyer at a time when it is requested and the vehicle 102 may directly benefit from a relevant reward 118. In some instances, the custom data selection 106 may be meaningful to a data buyer when multiple data from ECUs are included.

For example, the conditional request 114 for the particular data set 116 may include conditions related to a geographical location, a particular type (e.g., make, model, identification) of device, and/or a particular period of time, and the particular data set 116 requested may include data related to an operation of multiple ECUs of a vehicle 102, while the vehicle 102 is within the geographical location. Specifically, in this instance assume that a smart contract 112 includes the conditional request 114 of the data buyer is a particular data set 116 which includes data from ECUs measuring the power train, the brakes, the windshield wipers, and the fuel gauge, for a three hour period, within a 100 Km radius and the reward 118 is a discount on fuel within the 100 Km radius. The vehicle 102 may accept the smart contract 112 and create a custom data selection 106 including data collected for a three hour period within a 100 Km radius from the ECUs of the power train, the brakes, the windshield wipers, and the fuel gauge, and in exchange for the custom data selection 106 the vehicle may receive a reward 118 of discounted fuel from a fuel provider within the 100 Km radius. In this way, a data buyer may receive the custom data selection 106 which is relevant to the geographical location and the vehicle may be incentivized to provide the custom data selection 106 by receiving the reward 118 for a discount from a nearby fuel provider. In some examples, a device may preemptively accept a smart contract 112 prior to the availability of the custom data selection 106 to fulfil the conditional request 114.

For example, a smart contract 112 may include a conditional request 114 for a particular data set 116 including conditions related to a geographical location and the particular data set 116 requested may include data related to a performance of ECUs of the vehicle 102, while the vehicle 102 is within the geographical location. In this instance, assume that the performance may be a particular level of fuel or oil in the fuel tank and oil tank of the vehicle 102 within a 100 Km geographical radius and the reward 118 is a discount on fuel and/or maintenance for the vehicle 102. The smart contract 112 in this instance may be preemptively accepted and when the fuel level and/or oil level reaches the particular level of the conditional request 114 of the smart contract 112, the vehicle 102 may create the custom data selection 106 including the particular data set 116 requested. In exchange for fulfilling the smart contract 112 the reward may be issued to the vehicle 102. In this way, a data buyer may receive the custom data selection 106 which is relevant to the geographical location and the vehicle 102 may be incentivized to provide the custom data selection 106 by receiving the reward 118 for a discount from a nearby provider.

For example, a reward may be implementation or use of a function-on-demand of vehicle 102. That is, vehicle 102 may be equipped with functions, such as lane control, on-demand drive power (which can be controlled by programming through an ECU controlling the engine and/or electric motor of vehicle 102). Still other features of vehicle 102 may include subscription-based functions, such as satellite radio, on-demand safety support, etc. A driver of vehicle 102 may dislike forced lane control. In exchange for sharing a custom data selection in satisfaction of a particular data set 116 requested by a data buyer, the driver may be rewarded with an option to disable the lane control function. For example, reward 118 may a patch or executable code delivered to computing resource 104 and/or one or more ECUs of vehicle 102 that control the lane control function. Moreover, reward 118 may include a user interface aspect or element (such as additional code) allowing the driver to select implementation of the patch or executable code vis-a-vis a head unit or display of vehicle 102.

As another example, additional engine horsepower or motor kilowatt power (i.e., a temporary upgrade to operating function/functionality) can be achieved as a reward 118 for providing a custom data selection 106. That is, a drive power ECU of vehicle 102 may be programmable with respect to the amount of power output or generated by the engine or motor of vehicle 102. Accordingly, a reward may be an algorithm for changing a default torque profile of vehicle 102, a code for unlocking the algorithm (which in a default mode of vehicle 102, remains locked/unused), and may be stored in a memory associated with the drive power ECU or provided as part of reward 118.

It should be understood that, e.g., when collected data is streamed (as previously described), the on-demand function or enhancement may be controlled based on whether or not the collected data (custom data selection 106) is being captured/generated and released by vehicle 102/computing device 108 to decentralized entity 110. However, should that data stream stop or the custom data selection 106 no longer satisfy the particular data set 116, desired control, implementation, non-implementation of the function-on-demand may be lost, i.e., reward 118 may be revoked.

Further still, a reward need not be immediately or substantially, immediately provided or “redeemed” by the user or recipient of the reward. In some embodiments, rewards may comprise levels, tiers, or subsets of data, functionality, or other form of reward that can be accumulated. For example, FIG. 1 illustrates vehicle 102, computing device 108, and decentralized entity 110, each having a respective buffer, i.e., buffers 102, 109, and 119. R should be understood that not all these elements necessarily require a buffer. Desired operation, processing power, memory capabilities, etc. can dictate where a buffer is maintained. In some embodiments, rewards may be buffered. In some embodiments, captured data (e.g., most recent data, data comprising current data to data captured up to a determined point in time, total accumulated data, etc.) may be buffered. In some embodiments, the captured data and reward(s) may be maintained in the same buffer or different buffers. In some embodiments, different portions of the same buffer may be allocated to storing data and rewards separately.

It should be understood that the aforementioned buffers may be configured strictly as memory devices or data caches, but in some embodiments, may further comprise a counter or calculator functionality to determine how much reward (points, currency, etc.) a user is achieving and/or spending. Accordingly, buffers 103, 109, and/or 119 may comprise a reward accounting function. It should be understood that more than one buffer may reside in one or more of vehicle 102, computing device 108, and decentralized entity 110.

Referring to the function-on-demand examples described above, reward 118 may include points or levels of control afforded vehicle 102. For example, during a user's commute, reward points gained by sharing a custom data selection 106 that satisfies particular data set 116 may be received and accumulated in any one or more of buffers 103, 109, and 119. When a user of vehicle 102 wishes to redeem the accumulated and buffered points, the user may authorize the release of the points to enable (or disable) the desired function, desired control, etc. In some embodiments, one or more sensors 102 a may be used in a feedback fashion, whereby use of reward 118 may be premised upon the existence of favorable or appropriate conditions. For example, the use of increased horsepower (described above) may be effectuated or may be allowed for use when vehicle 102 is traveling along a section(s) of roadway that allow for faster travel speeds, such as a highway or section(s) of roadway sensed as having a relatively higher speed limit.

In some embodiments, buffered rewards (e.g., buffered points) may only be released commensurate with safety limitations. For example, similar to the above-described example, one or more sensors 102 a may detect (by sensing speed limit signs) that the speed limit of a currently-traveled section of roadway allows for only a subset of or less-than-maximum rewarded horsepower may be utilized. Accordingly, only the appropriate amount of buffered reward points may be used/released. Other checks may involve V2V or V2I communications to determine whether or not use of a reward 118 will be compliant with safety regulations or compliant with current travel conditions, neighboring traffic, etc.

Further regarding safety, sensors 102 a, which may sense driving characteristics of a particular user of vehicle 102 vis-a-vis braking actuation, acceleration profile, vehicle speed profile, and the like. These profiles or driving characteristics may be associated with a user by way of mobile device 105 being associated with the user and sensed as being present in vehicle 102, for example. The custom data selection 106 may be these characteristics/profiles which can be provided to a data buyer, such as an insurance carrier. The custom data selection 106 may comport with a particular data set 116 that the insurance carrier has specified to determine how to set or calculate insurance rates for particular drivers being provided insurance coverage. Insurance premiums may be set based on such data, where reward 118 may be lowered insurance premiums, insurance breaks, or other insurance-related incentives in exchange for data reflecting good or better driving behavior. Accordingly, reward 118 may also include improved user behavior. In this way, insurance may be dynamic, and/or follow a pay-as-you-drive model. Moreover, reward 118 may simply be access to reserved parking, available only to those drivers that share data and comport with safe driving behavior.

By the same token, a reward 118 may be a “negative reward” or punitive reaction. For example, unsafe or undesirable driving behavior may be captured by one or more sensors 102 a and provided as a custom data selection 106, and reward 118 may be increased insurance rates. It should be understood that a user of vehicle 102 may opt in to such a program, whereby rewards can be negative. When a user does not wish to participate (perhaps in anticipation of or being aware of his/her less-than-ideal driving behavior), rewards need not be provided. Accordingly, various embodiments may comprise a subscription-based or selective-participatory reward mechanism. As will be described below, computing resource 104 may search or monitor decentralized entity 110/computing device 108 for available smart contracts 112, and may choose to engage in a smart contract or not.

It should be understood that various embodiments may be used in association with a third-party ecosystem for the redemption of reward 118 in the form of points, vouchers, coupons, or other relevant currency or redeemable mechanism. For example, reward 118 may be free or reduced-fee media presented by a data buyer, or data buyer partner, such as a media content provider in exchange for a custom data selection 106 comprising media consumption data associated with a user or passenger of vehicle 102 over some period of time, at any given time, over a determined section(s) of roadway or traveled route, etc. The media consumption data may be provided by one or more sensors 102 a sensing usage of a radio or infotainment system of vehicle 102 (or through data/statistics/logs collected by or through computing device 108 or computing resource 104).

The examples described in connection with FIG. 1 describe rewards for custom data transmissions. A data buyer may fund a smart contract 112 with a reward 118 and request a particular data set 116 via the smart contract 112 deployed on a decentralized entity 110. A computing device 108, such as a MEC server may exist on nodes and be communicatively coupled to the decentralized entity 110 and a computing resource 104 (e.g., a CAN bus) on a vehicle 102. The computing device 108 may act to facilitate the reward 118 being transmitted to the vehicle 102 in exchange for the custom data selection 106. In this way, the data buyer may receive a specific custom data selection 106 which may be more valuable than wholesaled non-specific data, and the user/operator and/or the vehicle 102 may directly benefit by receiving a reward 118 in exchange for the specific custom data selection 106.

FIG. 2 illustrates an example system 200 including a computing device 208 for facilitating rewards for custom data transmissions consistent with the disclosure. FIG. 2 includes a data buyer 220 to provide a smart contract 212 with a conditional request 214 including a particular data set 216 and a reward 218. Although not shown in FIG. 2 so as to not obscure the examples of the disclosure, the smart contract 212 may be deployed on a decentralized entity such as the decentralized entity 110 of FIG. 1 (e.g., a blockchain with smart contract capabilities). FIG. 2 illustrates a computing device 208, a profile 222, a computing resource 204, and ECUs 224. Furthermore, FIG. 2 illustrates one or more buffers for buffering reward 218 or data meeting requirements of particular data set 216, e.g., buffer 205, 209, and 219. Although not illustrated in FIG. 2 as to not obscure examples of the disclosure, the computing resource 204 may be included in an edge device (e.g., the vehicle 102 of FIG. 1). In some examples the computing resource 204 may deploy the profile 222 on the computing device 208.

For example, the profile 222 may include information about the user/operator and/or the device (the vehicle 102) to which the computing resource 204 is deployed. In some embodiments, profile 222 may include information regarding the eco-footprint of the user/operator and/or vehicle 102. Information may include how often the user/operator uses vehicle 102, as well as how often the user/operator uses public transportation or (another more or less ecologically-conscious vehicle) associated with the user/operator via profile 222. For example, reward 218 may be provided based on how profile 222 changes, e.g., the more ecologically conscious the user/operator is being by using public transportation versus vehicle 102, reward 218 may increase or decrease. Reward 218 may include vouchers for public transportation, increased/decreased government subsidies, and the like.

In some embodiments, profile 222 may be used in conjunction with point-to-point embodiments of vehicle 102. That is, vehicle 102 may be a shared vehicle. However, when a user/operator/passenger is using vehicle 102, vehicle 102 acts that a particular instance of an edge device or edge data center specific to that user/operator/passenger who has an associated profile 222. In this way, custom data selections provided while a particular user/operator/passenger is using vehicle 102 are the reward 218 itself, i.e., the collection of data allows the user/operator/passenger to use that shared vehicle (or is it without payment or for reduced payment).

In some embodiments, the computing device 208 monitors the vehicle based on the profile 222 for available smart contracts 212 that may be accepted by the computing resource 204 via the profile 222. For example, a smart contract 212 may be funded with a reward 218 by the data buyer 220 in exchange for a custom data selection (e.g., the custom data selection 106) corresponding to the requested particular data set 216. The computing resource 204 may determine, via the profile 222 of the device (e.g., a vehicle) presented on a mobile device (e.g., a smart phone and/or a display included in the vehicle), that the conditional request 214 from the decentralized entity (e.g., via the smart contract 212) is a conditional request 214 from a data buyer 220. In some examples, an edge device (e.g., a vehicle) including a computing device 204 may generate a counter offer.

As used herein, the term “counter offer” refers to an offer made by the device in response to the receipt of a smart contract. For example, the computing device 204 may generate a counter offer which may include a change or modification to the conditional request 214 of the smart contract 212 offered by the data buyer 220. The counter offer may include alterations to the conditional request 214. The data buyer 220 may receive the counter offer from the computing resource 204 and the data buyer 220 may create a new smart contract 214 including the modified conditional requests 214 of the counter offer.

In some examples, an edge device (e.g., the vehicle 102 of FIG. 1) includes the computing resource 204 which may include machine learning capabilities. The profile 222 may include specifications corresponding to the edge device and/or an operator such that the computing resource 204 may automatically negotiate the conditional request 214 of a smart contract 212, based on the profile 222. Specifically, the computing resource 204 may automatically generate a counter offer, based on the specifications included on the profile 222, and the data buyer 220 may accommodate the counter offer by generating a new smart contract 212. The profile 222 may be displayed with information about the data buyer 220 such that the device may decline or accept the smart contract 212 that was created by the data buyer 220.

For example, the profile 222 may be displayed as an application on a smart phone, a tablet, a computing device, the display of a vehicle, etc. such that an available smart contract 212 may be viewed and accepted by an edge device (e.g., a vehicle). In some examples, the profile 222 may be utilized to create the custom data selection.

For example, the profile 222 via the computing resource 204 may accept, decline, and/or refrain from accepting, an available smart contract 212. The conditional request 214 of the smart contract 212 may include a particular data set 216 requested to include multiple data from the ECUs 224. The profile 222 may include options to select and deselect which ECUs, data points, data packages, and/or multiple data points (and/or data streams) from multiple ECUs, may be made available to the smart contract 212 via the computing device 208 such that the computing resource 204 via the profile 222 may create a custom data selection corresponding to the requested particular data set 216. In other words, the profile 222 may provide for the edge device to create a specific combination of ECU data and data buyers 220 to create a custom data selection. Specifically, FIG. 2 illustrates the profile 222 having options to select/deselect options e.g., ECU-1, ECU-2, ECU-3, ECU-4, and ECU-N where each of these options may correspond to a different ECU 224, and include data points, data packages, and/or multiple data points (and/or data streams) from multiple ECUs. In this way, the edge device (e.g., the vehicle 102) may create which data is shared with the data buyer 220 via the smart contract 212. In some examples, the edge device (e.g., the vehicle 102) may select/deselect a specific data buyer 220, categories of data buyers 220, and/or groups of data buyers 220 to share data.

An example category of data buyer 220 may be public service entities, manufacturing entities, retail entities, etc. A group of data buyers 220 may be data buyers 220 within a geographical area, data buyers 220 of the same company (e.g., gas stations of a particular company), data buyers 220 of the same retail establishment within a geographical area, etc. The profile may be utilized to select/deselect specific data buyers 220, groups of data buyers 220, or categories of data buyers 220. For example, FIG. 2 illustrates the profile 222 having options to select/deselect options e.g., DATA BUYER-1, DATA BUYER-2, DATA BUYER-3, DATA BUYER-4, and DATA BUYER-N where each of these options may correspond to a different data buyer 220, categories of data buyers 220, and/or groups of data buyers 220. In other words, the profile 222 may be used to control where the data compiled in the custom data selection is transmitted by selecting to include and/or exclude data buyers 220. In some examples, the profile 222 may collect and/or store the reward 218. In some examples, this storage may be accomplished by one or more of buffers 205, 209, and/or 219 which may be associated with profile 222.

The profile 222 may include a virtual repository to collect the reward 218 that may be funded to the smart contract 212 by the data buyer 220. The virtual repository may operate, as alluded to above, like a virtual wallet where an edge device (e.g., the vehicle 102) may store the reward 118. In this way, the edge device may use the reward 118 as they are collected or save them for a later time.

The examples described in connection with FIG. 2 describe a profile 222 which may be used to create a custom data selection in response to a request for a particular data set 216. In this way, the edge device (e.g., the vehicle 102) may control what data from the ECU may be shared and may directly benefit from the reward 218. Further, the data buyer 220 may benefit by receiving the custom data selection corresponding to the particular data set 216 per the smart contract 212. By utilizing the smart contract 212, the data buyer 220 may alter, change, delete, or otherwise amend the smart contract 212 to change the conditional request 214 and the particular data set 216 requested.

It should be understood that one or more aspects of the custom data selection, such as individual data elements or data sets/subsets making up the custom data selection may be weighted, ranked, or valued in certain ways. For example, custom data selections that comport with a hard-to-obtain particular data set 216 may be weighted more heavily/valued more than custom data selections that many vehicles or other edge devices are capable of providing/are already providing to a data buyer 220. Additionally, the accuracy or confidence associated with a custom data selection may also impact its value to data buyer 220. For example, vehicle 102 may include a particular sensor or set of sensors 102 a that are known to provide reliable data, and vehicle 102 is traveling in a relatively, sparsely-traveled area, the reward 218 for the custom data selection provided by vehicle 102 may be commensurately greater than that provided by another vehicle or edge device. Other vehicles or roadway infrastructure may verify or validate the value of data generated by vehicle 102.

In accordance with some embodiments, vehicle 102 may act as an edge hub, where vehicle 102 can be used to accomplish micro-jobs that can be paid vis-à-vis one or more forms of a reward 218. For example, the one or more sensors 102 a of vehicle 102 can measure, sense, or other collect data at a particular location, establishment, or area(s) that satisfy a particular data set 216 associated with a micro-job. In still other embodiments, reward 218 may relayed, returned to a data buyer 220, or forwarded as a donation to yet another third-party. For example, a location sensor of vehicle 102 may determine vehicle 102 is approaching or at a location where a donation of collected rewards, such as monetary rewards may be given. It may be determined (vis-à-vis profile 222) that the user of vehicle 102 prefers to donate to a particular charity, and when vehicle 102 approaches a physical location, such as a store associated with that charity, computing resource or computing device may electronically transfer monies associated with buffered rewards to that charity.

It should also be understood that data analytics and/or machine learning or artificial intelligence may be utilized in conjunction with various embodiments to predict the manner of reward 218 that can be provided in exchange for a custom data selection. Such methods and/or mechanisms may also be used to aggregate data, combine data from different sources (e.g., subsets of sensors 102 a) or data from different vehicles (shared at the edge vis-à-vis V2X communications or at computing device 208, at a decentralized entity, or other centralized entity in the cloud, for example).

In other embodiments, reward 218 may be protection for data. That is, a user or vehicle 102 may select certain data to share as a custom data selection in exchange for a reward 218 comprising protection for data that the user/vehicle 102 does not wish to share. In some embodiments, the more “other” data that is shared, the better the “private” data is protected. In some embodiments the other data may be considered data to be shared or that can be shared, e.g., non-private data. For example, such other data may comprise data that is an enabler for protecting/better protecting private data. For example, private data may include a driver's profile (e.g., driving behavior profile, vehicle preferences profile, etc.). When the driver enables or allows certain ECU(s)-related data to be captured and shared with a data buyer, such as GPS-data. vehicle operation/operational data, etc, to allow the data buyer to glean vehicle use/stress information for deriving or predicting a next service interval, the driver's profile(s) may be kept private. Accordingly, various data may be tagged, characterized, and/or otherwise identified as being private or non-private.

FIG. 3 illustrates an example flow chart 301 for rewards for custom data transmissions consistent with the disclosure. FIG. 3 illustrates a flow chart including many of the elements discussed herein in connection with FIGS. 1 and 2. However, the operations are not limited to a particular example described herein and may include additional operations such as those described with regard to the system 100 and 200 described in connection with FIGS. 1 and 2.

At block 330 a data buyer (e.g., the data buyer 220) may create a smart contract (e.g., the smart contract 112) including a conditional request (e.g., the conditional request 114) including a request for a particular data set (e.g., the particular data set 116), and the reward (e.g., the reward 118) offered to an edge device (e.g., the vehicle 102) in exchange for a custom data selection (e.g., the custom data selection 106) that fulfills the conditional request. For example, the data buyer may create the smart contract and publish it on a decentralized entity (e.g., the decentralized entity 110). The decentralized entity may be a blockchain with smart contract capabilities such that a smart contract may be stored once created by the data buyer. A smart contract may be changed by the data buyer when the data buyer creates a new smart contract. In this way, a smart contract may be created, modified, or otherwise updated. The smart contracts may be available to a computing device (e.g., the computing device 108) via a connection between the computing device and the decentralized entity.

For example, the computing device may be a MEC server which may exist on nodes. In this way, the computing device may be connected to a moving device (e.g., a vehicle) and the decentralized entity. An edge device such as a vehicle may include a computing resource (e.g., the computing resource 104) to monitor for available smart contracts. The computing device may monitor the computing resource based on the profile (e.g., the profile 222) for available smart contracts. For example, at block 332, the computing resource may via the profile, determine whether to accept the smart contract.

For example, the profile may display the smart contract and the information relating to the conditional request (e.g., the particular data set requested and the reward). When the vehicle (e.g., and/or an operator of a vehicle) declines the smart contract and the conditional request of the smart contract (“NO” at 334) the computing resource via the profile may refrain from accepting the smart contract at block 336. In another example, the computing resource may agree to accept the smart contract.

For example, the profile may display the smart contract and the information relating to the conditional request (e.g., the particular data set requested and the reward). When the vehicle (e.g., and/or an operator of a vehicle) accepts the smart contract and the conditional request of the smart contract (“YES” at 333) the computing resource via the profile may create a custom data selection based on the particular data set requested at block 335. For example, the computing resource may provide data from multiple ECUs and compile the data according to the conditional request of the smart contract. The computing resource of the vehicle may transmit the custom data selection to the computing device which may be connected to the computing resource and the decentralized entity.

For example, at block 338, the computing device may receive the custom data selection created by the vehicle in response to the conditional request of the smart contract. For example, the vehicle may transmit the custom data selection which corresponds to the particular data set requested by the smart contract. The custom data selection may be a specific selection of ECU data of the vehicle which may be valuable to the data buy who created the smart contract. In some examples, the computing device may authenticate the custom data selection.

For example, at block 340 the computing device may authenticate and apply a hash to the custom data selection. For example, the computing device may authenticate the custom data selection by providing a time stamp and/or other metadata to the custom data selection indicating when the selection was received, created, transmitted, details about the device that created the custom data selection etc. or combinations thereof. The computing device may apply a hash function to the custom data selection and the hash function may be stored with the transaction as an immutable record in the decentralized entity. The hash function applied to the custom data selection by the computing device may be compared to a hash function executed by the data buyer in response to the data buyer receiving the custom data selection from the vehicle via a side channel. The computing device may verify that the authenticated custom data selection fulfils the conditional request of the smart contract.

For example, at block 342, the smart contract may verify that the custom data selection corresponds to the particular data set requested and the conditional request (e.g., a particular GPS location, a particular time, etc.). For example, the custom data selection may be transmitted by the computing device to the decentralized entity to be verified by the smart contract. The smart contract may compare the authenticated custom data selection to the conditional request to determine if the particular data set requested was met by the custom data selection. In some examples, the custom data selection may not fulfill the smart contract.

For example, if the smart contract determines that the custom data selection does not fulfil the smart contract by providing the conditional data request, (“NO” at 344), the smart contract may refrain from releasing the reward to the computing device at 346. The custom data selection may not fulfill the smart contract when the conditional request of the smart contract is not complete. This instance may occur when the ECUs included in the custom data selection are not correct, and/or other conditional factors (e.g., GPS, time period, make/model/type of vehicle) are not correct. In other examples, the custom data selection may fulfill the smart contract.

For example, if the smart contract determines that the custom data selection does fulfil the smart contract by providing the conditional data request, (“YES” at 348), the vehicle, via the computing device may release the custom data selection to the data buyer and the data buyer via the smart contract may release the reward to the vehicle via the computing device at block 350. Specifically, the smart contract may verify that the custom data selection corresponds to the particular data set and the conditional requests of the smart contract. This instance may occur when the ECUs included in the custom data selection not correct (the same as the particular data set requested), and/or other conditional factors (e.g., GPS, time period, make/model/type of vehicle) are correct. In some examples, the computing device may store the hash function of the custom data selection as an immutable record in a blockchain.

In some embodiments, as described above, prior to releasing or refraining from releasing the reward, the reward may be validated or otherwise processed at operation 343. Processing, in some embodiments, may comprise determining an appropriate reward for the custom data selection. For example, one or more of the computing resource 104, mobile device 105, computing device 108, or decentralized entity 110 may access a listing, table, or other mapping of rewards to custom data selection. In some embodiments an appropriate reward(s) may be algorithmically determined based on a value of or custom data selection type, identifier, or other characterization thereof. For example, and as described above, the reliability or how well the custom data selection meets the parameter(s) of the particular data set/conditional request may be considered. For example, a value or indication of this reliability and/or how well the parameter(s) are met can be assigned to the custom data set. It should be understood that reliability and “wellness” can be the same/similar, or they may refer to different standards or characteristics. For example, reliability/wellness can refer to how well parameters set forth in a data request, for example, are met. However, reliability (as opposed to wellness), can in some embodiments, refer to the reliability, accuracy, or other characteristic(s) of the data source, or whether the data has been/can be verified. For example, a data value making up the custom data selection generated by a solitary in-vehicle sensor may be deemed to be less reliable that a data value obtained from several sources, e.g., by the in-vehicle sensor and from external, e.g., smart roadway infrastructure sensors). That is, vehicle speed, for example, can be determined by one or more in-vehicle sensors capable of sensing axle rotation and wheel rotation. Vehicle speed may also be determinable by external radar sources, e.g., radar sources located at two traffic lights between which the vehicle travels. Other measures of reliability may be associated with known accuracy of certain data sources or sensors, such as data obtained by extrapolating engine rotation speed, and actual wheel speed determined vis-a-vis a wheel rotation sensor.

Reliability may be determined based on type of data identified in the custom data selection, where data type can be related to or dependent on the source of the data. For example, a data request or smart contract may specify preferred sources of data, and the custom data selection may include data source identifiers associated with each data element making up the custom data selection. In some embodiments, expected data values and/or ranges may be specified in the data request, smart contract. etc., in which case certain prior to forwarding the custom data selection, or upon/after receipt of the custom data selection, any one or more of computing resource 104, mobile device 105, computing device 108, or decentralized entity 110 can compare the custom data selection values/ranges to the specified data values/ranges. Still other methods of determining or ascertaining data reliability or wellness may be implemented in accordance with various embodiments, such as but not limited to various forms of machine learning/artificial intelligence for comparing and determining data reliability. Depending on the reliability and/or how well the custom data set meets the parameter(s) a particular reward can be selected in exchange for the custom data set, e.g., the more reliable the custom data set is determined to be, the better or more valuable the reward given. In some embodiments, processing can also comprise weighting of the custom data selection or certain data making up the custom data selection. The weighting may be applied, e.g., by computing resource 104, mobile device 105, computing device 108, and/or decentralized entity 110, and the applied weighting may dictate the reward to be released, the holding back of the reward, or the amount/extent of the reward that is to be released.

In other embodiments, as also alluded to above, certain considerations may be taken into account regarding the direction in which the reward is to be released. For example, the reward may “return” to the user that generated or authorized the generation of the custom data selection, e.g., in terms of data protection, monetary award, etc. In other examples, the reward may be “forwarded” to a third party, such as a charity, third-party ecosystem, etc. For example, in terms of a function-on-demand for a vehicle, e.g., vehicle 102, processing the reward at operation 343 may comprise determining how much horsepower can be added and/or used, what media can be freely accessed, how many points can be collected, etc. In still other embodiments, processing the reward at operation 343 may entail buffering or aggregating rewards, performing accounting functions regarding rewards, and the like. Further still, validating a reward at operation 343 may comprise determining the reliability, rarity, or other characteristic(s) of the custom data selection which in turn is reflected by a commensurately appropriate reward.

For example, at block 352, the computing device may store the hash function of the custom data selection and the transaction as an immutable record in the decentralized entity. Specifically, the computing device may store the outcome and/or information about the vehicle as an immutable record with the transaction information in the blockchain. The custom data selection may also be stored in the profile corresponding to the vehicle on the computing device.

The examples described in connection with FIG. 3 describe rewards for custom data transmissions. A data buyer may fund a smart contract with a reward and request a particular data set via the smart contract deployed on a decentralized entity. A computing device, such as a MEC server may exist on nodes and be communicatively coupled to the decentralized entity and a computing resource (e.g., a CAN bus) on a vehicle. The computing device may act to facilitate the reward being transmitted to the vehicle in exchange for the custom data selection. In this way, the data buyer may receive a specific custom data selection which may be more valuable than wholesaled non-specific data, and the user/operator and/or the vehicle may directly benefit by receiving a reward in exchange for the specific custom data selection.

FIG. 4 illustrates an example flow diagram 403 for rewards for custom data transmissions consistent with the disclosure. FIG. 4 illustrates a device such as a vehicle 402, a computing resource 404 (e.g., a CAN bus), a profile 422, a computing device 408 (e.g., a MEC server), a decentralized entity 410 (e.g., a blockchain) a smart contract 412, and a data buyer 420. The profile 422 may include information about the vehicle 402 such as the make, model, vehicle identification number, an owner, an operator, etc. The profile 422 may be displayed as an application on a mobile device (e.g., and/or other computing device such as a display within the vehicle) and functions relating to the creation of a custom data selection (e.g., the custom data selection 106) may be manipulated and controlled via the profile. In some examples, the profile may be shared with the computing device 408.

For example, at block 460 the vehicle 402 may share the profile 422 with the computing device 408 such that the computing device 408 may access information related to the profile 422. For example, the computing device 408 may determine if the vehicle 402 is monitoring for available smart contracts 412. Smart contracts 412 may be monitored on the computing device 408 when the smart contracts are deployed on the decentralized entity 410 by the data buyer 420.

For example, at 462 a data buyer 420 may create a smart contract 412 to include a conditional request (e.g., the conditional request 114) for a particular data set (e.g., the particular data set 116) and a reward (e.g., the reward 118) in exchange for a custom data selection (e.g., the custom data selection 106) from the vehicle 402. The smart contract 412 created by the data buyer 420 may be deployed on a decentralized entity 410 and available to the computing device 408.

For example, at 464 the computing device 408 may receive the smart contract 412 including the information included in the conditional request (e.g., the particular data set and the reward). In some examples, the vehicle 402 may use the profile 422 to monitor for smart contracts 412 that the vehicle 402 may have the capability to fulfill in exchange for the reward. For example, at block 466 the vehicle 402 may monitor the computing device for available smart contracts, based on the profile 422, and the vehicle may agree to the conditional request of the smart contract 412.

The computing device 408 may receive a notification that the vehicle 102 has agreed to the conditional request of the smart contract 112. In response to the agreement, at block 468, the computing device 408 may transmit conditional request of the smart contract 412 to the vehicle 402. For example, the computing resource 404 may receive the conditional request of the smart contract 412 and create the custom data selection to fulfill the particular data request of the smart contract 412.

For example, the vehicle 402 may create a custom data selection to fulfil the smart contract 412. In some examples, the profile 422 may be utilized to select and/or deselect a single ECU and/or multiple ECUs such that the data of the selected ECU(s) may be compiled into a custom data selection. Additionally, the profile 422 may be utilized to comply with other conditional requests (e.g., a particular time, or a particular location, etc.). In another example, the profile 422 may be utilized to preemptively agree to the smart contract 412 and instruct that the smart contract 412 may be executed when the data from the ECUs requested by the smart contract 412 becomes available. In yet another example, the profile 422 may be utilized by the computing device to collect data from ECU(s) for a period of time such that a stream of data may be created for the custom data selection. The vehicle 102 via the computing resource 404 may transmit the custom data selection to the computing device 408.

For example, at block 470, the vehicle 402 may transmit the custom data selection to the computing device 408. For example, the computing device 408 may receive the custom data selection 408 and authenticate the custom data selection. For example, the computing device may apply a time stamp to the custom data selection and apply a hash function to the custom data selection. The hash function may secure the custom data selection such that it may not be altered or tampered with. In this way, at block 471, the hash function may be stored with the transaction as an immutable record on the decentralized entity 410. The custom data selection may be verified by the computing device 408 and/or the smart contract 412. In other words, the computing device 408 may verify the custom data selection via the smart contract 412 on the decentralized entity 410. For example, the smart contract 412 may receive the custom data selection and compare the authenticated contents to the conditional request of the smart contract 412. In this way, the computing device 408 may determine if the custom data selection fulfils the smart contract 412. The vehicle 402, via the computing device 408 may transmit the custom data selection to the data buyer 420 via a side channel.

For example, at block 474, the vehicle 402 via the computing device 408 may transmit the custom data selection to the data buyer 420. The data buyer 420 may execute another hash function on the received custom data selection and compare it to the hash function stored as a record in the decentralized entity 410. The resulting hash value indicating that the hash functions are the same indicate to the data buyer 420 that the received custom data selection does not include an error (e.g., or other changes).

If the contents of the custom data selection fulfills the conditional request of the smart contract 412, the data buyer 420 may at block 476 execute the release of the reward via the smart contract 412. The smart contract 412 may transmit the reward to the computing device 408. In other words, at block 478, the smart contract 412 may transmit the reward to the computing device 408 in response to the custom data selection fulfilling the conditional request and the particular data set requested. In this way, the data buyer 420 may receive accurate, customized data in exchange for a reward of which the vehicle 402 may directly benefit.

For example, at block 478, the smart contract 412 may release/transmit the reward to the vehicle 402 via the computing device 408 in response to the custom data selection having fulfilled the conditional request of the smart contract 412. In response to receiving the reward, the computing device 408 may transmit the reward to the vehicle 402. For example, at block 480, the computing device 408 may transmit the reward to the vehicle 402. The profile 422 may include a virtual wallet associated with the vehicle 402, an owner, and/or an operator such that the reward may be stored and/or redeemed. The computing device 408 may store the transaction as a record in the decentralized entity 410.

The examples described in connection with FIG. 4 describe rewards for custom data transmissions. A data buyer 420 may fund a smart contract 412 with a reward and request a particular data set via the smart contract 412 deployed on a decentralized entity 410. A computing device 408, such as a MEC server may exist on nodes and be communicatively coupled to the decentralized entity 410 and a computing resource 402 (e.g., a CAN bus) on a vehicle. The computing device 408 may act to facilitate the reward being transmitted to the vehicle 402 in exchange for the custom data selection. In this way, the data buyer 420 may receive a specific custom data selection which may be more valuable than wholesaled non-specific data, and the user/operator and/or the vehicle 402 may directly benefit by receiving a reward in exchange for the specific custom data selection.

FIG. 5 illustrates an example of a non-transitory machine-readable memory resource 582 and processing resource 584 for rewards for custom data transmissions consistent with the disclosure. Although not illustrated in FIG. 5 as to not obstruct the examples of the disclosure, the processing resource 584 and the memory resource 582 may be included in a computing device (e.g., the computing device 108). The processing resource 584 may be a hardware processing unit such as a microprocessor, microcontroller, application specific instruction set processor, coprocessor, network processor, or similar hardware circuitry that may cause machine-readable instructions to be executed. In some examples, the processing resource 584 may be a plurality of hardware processing units that may cause machine-readable instructions to be executed. The processing resource 584 may include central processing units (CPUs) among other types of processing units. The memory resource 582 may be any type of volatile or non-volatile memory or storage, such as random-access memory (RAM), flash memory, read-only memory (ROM), storage volumes, a hard disk, or a combination thereof.

The memory resource 582 may store instructions thereon, such as instructions 586, 588, 590, 592, 594, and 596. When executed by the processing resource 584, the instructions may cause the computing device to perform specific tasks and/or functions. For example, the memory resource 582 may store instructions 586 which may be executed by the processing resource 584 to cause the computing device to receive a conditional request (e.g., the conditional request 114) from a decentralized entity (e.g., the decentralized entity 110) for a particular data set (e.g., the particular data set 116) from a vehicle (e.g. the vehicle 102). For example, a smart contract (e.g., the smart contract 112) may be created by a data buyer (e.g., the data buyer 220) indicating a conditional request for a custom data selection (e.g. the custom data selection 106) that corresponds to the particular data set which may be exchanged for a reward (e.g., the reward 118). The smart contract may be funded by the data buyer and deployed on the decentralized entity. The computing device may be communicatively connected to both the vehicle and the decentralized entity to facilitate the exchange of a custom data selection for a reward.

For example, the memory resource 582 may store instructions 588 which may be executed by the processing resource 584 to cause the computing device to receive an agreement from the vehicle responsive to the conditional request from the decentralized entity for the particular data set. For example, the vehicle may include a profile (e.g., the profile 222) which may be shared with the computing device to monitor the computing device for available smart contracts. The computing resource of the vehicle may transmit an agreement from the vehicle to the computing device when the vehicle agrees to the conditional request of the smart contract where the conditional request and the smart contract may be available as data on the profile. The vehicle includes a computing resource (e.g., the computing resource 104) which may be a CAN bus. The computing resource may prepare a custom data selection from a single or multiple ECUs of the vehicle. The custom data selection corresponds to the particular data selection and the profile may be used to select and deselect the ECUs requested in the particular data set such that the custom data selection may be created and transmitted to the computing device.

For example, the memory resource 582 may store instructions 590 which may be executed by the processing resource 584 to receive a custom data selection based on the conditional request for the particular data set. In other words, the computing device may receive the created custom data selection from the vehicle. The computing device may authenticate the custom data selection by adding a time stamp and applying a hash function to the custom data selection such that it may be stored with the transaction as an immutable record.

For example, the memory resource 582 may store instructions 592 which may be executed by the processing resource 584 to apply a hash function to the custom data selection provided by the vehicle. The hash function may be used to secure the custom data selection and may be stored as part of an immutable record in the decentralized entity. The computing device may verify that the custom data selection fulfils the conditional request of the smart contract.

For example, the memory resource 582 may store instructions 594 which may be executed by the processing resource 584 to transmit the custom data selection to the decentralized entity to verify that the custom data selection fulfills the conditional request. In other words, the computing device may transmit the custom data selection to the smart contract deployed on the decentralized entity. Specifically, the smart contract may receive the hashed custom data selection and compare the authenticated contents to the conditional request of the smart contract. The vehicle may, via the computing device, transmit the custom data selection to the data buyer using a side channel. The data buyer may execute a hash function on the received custom data selection to identify if there has been an error in transmission. The transaction between the vehicle and the data buyer may be stored by the computing device as an immutable record with the hash function executed by the computing device on the blockchain of the decentralized entity.

For example, the memory resource 582 may store instructions 596 which may be executed by the processing resource 584 to store the hash function of the custom data selection with a transaction record in the decentralized entity. For example, the hash function may be stored with the transaction as an immutable record. In other words, a hash function corresponding to the custom data selection may be stored as a block in the blockchain of the decentralized entity.

The examples described in connection with FIG. 5 describe rewards for custom data transmissions. A data buyer may fund a smart contract with a reward and request a particular data set via the smart contract deployed on a decentralized entity. A computing device, such as a MEC server may exist on nodes and be communicatively coupled to the decentralized entity and a computing resource (e.g., a CAN bus) on a vehicle. The computing device may act to facilitate the reward being transmitted to the vehicle in exchange for the custom data selection. In this way, the data buyer may receive a specific custom data selection which may be more valuable than wholesaled non-specific data, and the user/operator and/or the vehicle may directly benefit by receiving a reward in exchange for the specific custom data selection.

FIG. 6 illustrates an example method 685 for rewards for custom data transmissions consistent with the disclosure. At 689, receiving, by a computing device (e.g., the computing device 108), a conditional request from a decentralized entity (e.g., the decentralized entity 110) for a particular data set (e.g., the particular data set 116), wherein the decentralized entity defines conditions for the particular data set. In other words, a smart contract (e.g., the smart contract 112) included on the decentralized entity may request the exchange of a custom data selection (e.g., the custom data selection 106) and the reward (e.g., the reward 118). In some examples, the smart contract may provide the conditional request to the computing device for a particular data set from a vehicle (e.g., the vehicle 102), wherein the conditional request includes information about the reward offered in exchange for the receipt of the custom data selection. The computing device may receive an agreement from the vehicle to provide the particular data set by creating a custom data selection.

For example, at block 691, receiving, by the computing device from a vehicle, an agreement to fulfill the conditional request for the particular data set. For example, the vehicle may include a profile (e.g., the profile 222) which may be shared with the computing device to monitor the computing device for available smart contracts. The computing device may determine via the profile of a vehicle displayed on a mobile device (e.g., a smart phone and/or a display in the vehicle), that the conditional request from the decentralized entity is a conditional request from a data buyer (e.g., the data buyer 220). The vehicle may determine whether to share the conditional requested data with the data buyer requesting it. In other words, a computing resource (e.g., the computing resource 104) of the vehicle may transmit an agreement from the vehicle to the computing device when the vehicle agrees to the conditional request of the smart contract. The vehicle includes the computing resource which may be a CAN bus to create the custom data selection.

For example, at block 693, receiving, by the computing device from the vehicle, a custom data selection based on the conditional request for the particular data set. The computing resource may prepare a custom data selection from a single or multiple ECU(s) of the vehicle. The custom data selection corresponds to the particular data selection and the profile may be used to select and deselect the ECUs requested in the particular data set such that the custom data selection may be created and transmitted to the computing device. The computing device may authenticate the custom data selection by applying a time stamp to indicate when the custom data selection was received and/or created and to secure the data for verification. The computing device may apply a hash function to the custom data selection provided by the vehicle.

For example, at block 695, applying by the computing device, a hash function to the custom data election provided by the vehicle. The hash function may be stored as an immutable record in the blockchain with the transaction record. The hash function may provide a way to verify that the custom data selection transmitted to the data buyer from the vehicle has not been tampered with or altered. Specifically, the vehicle may transmit the custom data selection via the computing device, to the data buyer utilizing a side channel. The data buyer may execute a new hash function and compare the new hash function to the hash function applied by the computing device. If the hash functions are the same (e.g., a hash value), the custom data selection received from the vehicle has not been altered. Thus, it is the same custom data selection that has been authenticated. The computing device may verify the contents of the custom data selection to the smart contract.

For example, at block 697, transmitting, by the computing device, the custom data selection to the decentralized entity to verify that the conditional request for the particular data set are fulfilled by the custom data selection. In other words, the computing device may transmit the custom data selection to the smart contract deployed on the decentralized entity. Specifically, the smart contract may receive the custom data selection and compare the authenticated contents to the conditional request of the smart contract. The computing device may transmit the reward to the vehicle when the conditional requests are met.

In some examples, at block 699, transmitting, by the computing device, a reward from the decentralized entity to the vehicle in response to the custom data selection having fulfilled the conditional request. For example, if the contents of the custom data selection fulfill the conditional request of the smart contract, the smart contract may transmit the reward to the computing device. Specifically, the particular data set requested by the decentralized entity may be related to biometric sensor data collected while the vehicle is in a geographical area, and the reward provided to the vehicle may be information about entities existing within the geographical area. The transaction between the vehicle and the data buyer may be stored by the computing device as an immutable record on the blockchain of the decentralized entity.

It should be understood that although various embodiments have been described in the context of a vehicle, such as a automobile, various embodiments can be used in the context of drones or other manned and unmanned vehicles or apparatuses. For example, a business utilizing or providing drone delivery can share custom data selections (e.g., collected visual data) with an interested data buyer. As another example, zero dollar vehicles can be realized by sharing data collected by one or more sensors in or associated with such vehicles. That is, by allowing such vehicles to collect data and share that collected data with one or more data buyers, the vehicles can pay for themselves. Accordingly, users of such vehicles need not pay any fees for using such vehicles. Alternatively, or in addition, use of certain vehicles, such as paid public transportation can be free, when a user elects to share data, e.g., from a mobile device (such as mobile device 105) upon entering the public transportation vehicle.

In the foregoing detailed description of the disclosure, reference is made to the accompanying drawings that form a part hereof, and in which is shown by way of illustration how examples of the disclosure may be practiced. These examples are described in sufficient detail to enable those of ordinary skill in the art to practice the examples of this disclosure, and it is to be understood that other examples may be utilized and that process, electrical, and/or structural changes may be made without departing from the scope of the present disclosure.

As used herein, the designator “N”, particularly with respect to reference numerals in the drawings, indicates that a plurality of the particular feature so designated can be included with examples of the disclosure. The designators can represent the same or different numbers of the particular features. Further, as used herein, “a plurality of” an element and/or feature can refer to more than one of such elements and/or features.

The figures herein follow a numbering convention in which the first digit corresponds to the drawing figure number and the remaining digits identify an element or component in the drawing. Elements shown in the various figures herein may be capable of being added, exchanged, and/or eliminated so as to provide a number of additional examples of the disclosure. In addition, the proportion and the relative scale of the elements provided in the figures are intended to illustrate the examples of the disclosure and should not be taken in a limiting sense. 

What is claimed:
 1. An edge computing system comprising: a first edge computing device to transmit data from an edge hub device provisioned with a plurality of hardware computing resources to a decentralized entity, the first edge computing device is configured to: receive a custom data selection from the edge hub device in response to a conditional request for a particular data set by the decentralized entity; verify that the custom data selection fulfills the conditional request of the decentralized entity; transmit the custom data selection to the decentralized entity; determine an appropriate reward based on one or more characteristics of the custom data selection; and transmit the appropriate reward to a recipient from the decentralized entity in response to the custom data selection having fulfilled the conditional request.
 2. The edge computing system of claim 1, wherein the first edge computing device is further configured to determine the one or more characteristics of the custom data selection.
 3. The edge computing system of claim 2, wherein the one or more characteristics of the custom data selection comprises at least one of a reliability of the custom data selection and how well the custom data selection fulfills the conditional request.
 4. The edge computing system of claim 3, further comprising determining reliability of the custom data selection based on at least one of accuracy associated with one or more sources providing the data, and a number of different ones of the one or more sources providing the data.
 5. The edge computing system of claim 4, wherein the one or more sources comprise at least one of a data source local to the edge hub device and a data source external to the edge hub device.
 6. The edge computing system of claim 3, further comprising comparing at least one of data values and data ranges comprising the custom data selection with at least one of data values and data ranges set forth in the conditional request, and determining closeness of the at least one of the data values and data ranges comprising the custom data selection with the at least one of the data values and the data ranges set forth in the conditional request.
 7. The edge computing system of claim 2, wherein the one or more characteristics of the custom data selection comprise weight values assigned to data or data subsets comprising the custom data selection.
 8. The edge computing system of claim 1, wherein the first edge computing device verifies that the custom data selection fulfills the conditional request based on comparison data received from the edge hub device.
 9. The edge computing system of claim 8, wherein the comparison data comprises a comparison between sensor data generated by one or more sensors of the edge hub device and data generated by at least one of other edge hub devices and infrastructure devices.
 10. The edge computing system of claim 9, wherein the edge hub device comprises a first vehicle, the other edge hub devices comprise neighboring vehicles, and the infrastructure devices comprise smart roadway infrastructure.
 11. The edge computing system of claim 10, wherein the reward comprises control or level of control of an on-demand vehicle function.
 12. The edge computing system of claim 10, wherein the reward comprises a temporary upgrade to a vehicle operating functionality including at least one of a software patch, executable computer code, and an access code.
 13. The edge computing system of claim 1, wherein one of the first edge computing device or the decentralized entity is configured to revoke the reward or scale the reward in response to the custom data selection no longer fulfilling the conditional request.
 14. The edge computing system of claim 1, wherein the reward comprises one of a monetary reward and a non-monetary reward.
 15. The edge computing system of claim 1, wherein the recipient comprises the edge hub device or a third-party recipient.
 16. The edge computing system of claim 1, wherein the reward comprises a redeeming mechanism redeemable at a third-party transaction ecosystem.
 17. The edge computing system of claim 1, wherein at least one of the first edge computing system, the edge hub device, and the decentralized entity comprise, in part, a buffer configured to buffer the reward, a subset of the reward, or an accumulation of rewards.
 18. The edge computing system of claim 17, wherein the buffer comprises an accounting function configured to monitor and calculate reward accumulation and redemption.
 19. The edge computing system of claim 17, wherein the buffer is further configured to store at least one of a most recent custom data selection, and an accumulation of current and past custom data selections.
 20. The edge computing system of claim 20, wherein the decentralized entity releases one of a portion of the reward, the subset of the reward, or a portion of the accumulated rewards based on at least one of a degree to which the custom data selection fulfills the conditional request, and an external operating condition relevant to the edge hub device. 